Association of circulating metabolic biomarkers with risk of lung cancer: a population-based prospective cohort study - Lan Wu; Jun Yang; Yu Chen; Jiahao Lin; Wenkai Huang; Mengmeng Li (BMC Medicine)
Abstract Background There is emerging evidence that metabolites might be associated with risk of lung cancer, but their relationships have not been fully characterized. We aimed to investigate the association between circulating metabolic biomarkers and lung cancer risk and the potential underlying pathways. Methods Nuclear magnetic resonance metabolomic profiling was conducted on baseline plasma samples from 91,472 UK Biobank participants without cancer and pregnancy. Multivariate Cox regression models were employed to assess the hazard ratios (HRs) of 164 metabolic biomarkers (including metabolites and lipoprotein subfractions) and 9 metabolic biomarker principal components (PCs) for lung cancer, after adjusting for covariates and false discovery rate (FDR). Pathway analysis was conducted to investigate the potential metabolic pathways. Results During a median follow-up of 11.0 years, 702 participants developed lung cancer. A total of 109 metabolic biomarkers (30 metabolites and 79 lipoprotein subfractions) were associated with the risk of lung cancer. Glycoprotein acetyls demonstrated a positive association with lung cancer risk [HR = 1.13 (95%CI: 1.04, 1.22)]. Negative associations with lung cancer were found for albumin [0.78 (95%CI: 0.72, 0.83)], acetate [0.91 (95%CI: 0.85, 0.97)], valine [0.90 (95%CI: 0.83, 0.98)], alanine [0.88 (95%CI: 0.82, 0.95)], glucose [0.91 (95%CI: 0.85, 0.99)], citrate [0.91 (95%CI: 0.85, 0.99)], omega-3 fatty acids [0.83 (95%CI: 0.77, 0.90)], linoleic acid [0.83 (95%CI: 0.77, 0.89)], etc. Nine PCs represented over 90% of the total variances, and among those with statistically significant estimates, PC1 [0.85 (95%CI: 0.80, 0.92)], PC2 [0.88 (95%CI: 0.82, 0.95)], and PC9 [0.87 (95%CI: 0.80, 0.93)] were negatively associated with lung cancer risk, whereas PC7 [1.08 (95%CI: 1.00, 1.16)] and PC8 [1.16 (95%CI: 1.08, 1.26)] showed positive associations with lung cancer risk. The pathway analysis showed that the “linoleic acid metabolism” was statistically significant after the FDR adjustment (p value 0.0496). Conclusions Glycoprotein acetyls had a positive association with lung cancer risk while other metabolites and lipoprotein subfractions showed negative associations. Certain metabolites and lipoprotein subfractions might be independent risk factors for lung cancer. Our findings shed new light on the etiology of lung cancer and might aid the selection of high-risk individuals for lung cancer screening.